CIFW02 — Causal identification and discovery

Graphical models have been shown to be a powerful tool for addressing a wide range of problems, including identification of statistical parameters under confounding, selection effects, and missing data, the study of social network data, genomics, and analyses of systems of entangled particle state systems arising in quantum theory. This workshop will bring together methodological and applied researchers working on the theory of graphical models, and their applications. The goal of the workshop is to both exhibit recent advances in the theory of graphical models and to showcase existing connections to applications, as well as to discover new ones.